Given an input image, the goal of object detection is to find the bounding boxes and their corresponding classes for objects of interests in the image. To tackle this task, various object detection models based on conventional convolutional neural networks (CNNs), including Faster R-CNN [1]} and YOLO [2]}, to recent transformer-based [3]} models, such as DETR [4]} and Deformable DETR [5]}, are proposed, showing remarkable performances. In other words, there have been considerable attentions to search for new architectures, for improving their performances on various object detection tasks, for example, finding objects in aerial images from Earth Vision [6]}.
